MLIR

Multi-Level IR Compiler Framework

'affine' Dialect

This dialect provides a powerful abstraction for affine operations and analyses.

Polyhedral Structures

MLIR uses techniques from polyhedral compilation to make dependence analysis and loop transformations efficient and reliable. This section introduces some of the core concepts that are used throughout the document.

Dimensions and Symbols

Dimensions and symbols are the two kinds of identifiers that can appear in the polyhedral structures, and are always of index type. Dimensions are declared in parentheses and symbols are declared in square brackets.

Examples:

// A 2d to 3d affine mapping.
// d0/d1 are dimensions, s0 is a symbol
#affine_map2to3 = affine_map<(d0, d1)[s0] -> (d0, d1 + s0, d1 - s0)>

Dimensional identifiers correspond to the dimensions of the underlying structure being represented (a map, set, or more concretely a loop nest or a tensor); for example, a three-dimensional loop nest has three dimensional identifiers. Symbol identifiers represent an unknown quantity that can be treated as constant for a region of interest.

Dimensions and symbols are bound to SSA values by various operations in MLIR and use the same parenthesized vs square bracket list to distinguish the two.

Syntax:

// Uses of SSA values that are passed to dimensional identifiers.
dim-use-list ::= `(` ssa-use-list? `)`

// Uses of SSA values that are used to bind symbols.
symbol-use-list ::= `[` ssa-use-list? `]`

// Most things that bind SSA values bind dimensions and symbols.
dim-and-symbol-use-list ::= dim-use-list symbol-use-list?

SSA values bound to dimensions and symbols must always have ‘index’ type.

Example:

#affine_map2to3 = affine_map<(d0, d1)[s0] -> (d0, d1 + s0, d1 - s0)>
// Binds %N to the s0 symbol in affine_map2to3.
%x = alloc()[%N] : memref<40x50xf32, #affine_map2to3>

Restrictions on Dimensions and Symbols

The affine dialect imposes certain restrictions on dimension and symbolic identifiers to enable powerful analysis and transformation. A symbolic identifier can be bound to an SSA value that is either an argument to the function, a value defined at the top level of that function (outside of all loops and if operations), the result of a constant operation , or the result of an affine.apply operation that recursively takes as arguments any symbolic identifiers, or the result of a dim operation on either a memref that is a function argument or a memref where the corresponding dimension is either static or a dynamic one in turn bound to a symbolic identifier. Dimensions may be bound not only to anything that a symbol is bound to, but also to induction variables of enclosing affine.for operations , and the result of an affine.apply operation (which recursively may use other dimensions and symbols).

Affine Expressions

Syntax:

affine-expr ::= `(` affine-expr `)`
              | affine-expr `+` affine-expr
              | affine-expr `-` affine-expr
              | `-`? integer-literal `*` affine-expr
              | affine-expr `ceildiv` integer-literal
              | affine-expr `floordiv` integer-literal
              | affine-expr `mod` integer-literal
              | `-`affine-expr
              | bare-id
              | `-`? integer-literal

multi-dim-affine-expr ::= `(` `)`
                        | `(` affine-expr (`,` affine-expr)* `)`

ceildiv is the ceiling function which maps the result of the division of its first argument by its second argument to the smallest integer greater than or equal to that result. floordiv is a function which maps the result of the division of its first argument by its second argument to the largest integer less than or equal to that result. mod is the modulo operation: since its second argument is always positive, its results are always positive in our usage. The integer-literal operand for ceildiv, floordiv, and mod is always expected to be positive. bare-id is an identifier which must have type index . The precedence of operations in an affine expression are ordered from highest to lowest in the order: (1) parenthesization, (2) negation, (3) modulo, multiplication, floordiv, and ceildiv, and (4) addition and subtraction. All of these operators associate from left to right.

A multidimensional affine expression is a comma separated list of one-dimensional affine expressions, with the entire list enclosed in parentheses.

Context: An affine function, informally, is a linear function plus a constant. More formally, a function f defined on a vector $$\vec{v} \in \mathbb{Z}^n$$ is a multidimensional affine function of $$\vec{v}$$ if $$f(\vec{v})$$ can be expressed in the form $$M \vec{v} + \vec{c}$$ where $$M$$ is a constant matrix from $$\mathbb{Z}^{m \times n}$$ and $$\vec{c}$$ is a constant vector from $$\mathbb{Z}$$. $$m$$ is the dimensionality of such an affine function. MLIR further extends the definition of an affine function to allow ‘floordiv’, ‘ceildiv’, and ‘mod’ with respect to positive integer constants. Such extensions to affine functions have often been referred to as quasi-affine functions by the polyhedral compiler community. MLIR uses the term ‘affine map’ to refer to these multidimensional quasi-affine functions. As examples, $$(i+j+1, j)$$, $$(i \mod 2, j+i)$$, $$(j, i/4, i \mod 4)$$, $$(2i+1, j)$$ are two-dimensional affine functions of $$(i, j)$$, but $$(i \cdot j, i^2)$$, $$(i \mod j, i/j)$$ are not affine functions of $$(i, j)$$.

Affine Maps

Syntax:

affine-map-inline
   ::= dim-and-symbol-id-lists `->` multi-dim-affine-expr

The identifiers in the dimensions and symbols lists must be unique. These are the only identifiers that may appear in ‘multi-dim-affine-expr’. Affine maps with one or more symbols in its specification are known as “symbolic affine maps”, and those with no symbols as “non-symbolic affine maps”.

Context: Affine maps are mathematical functions that transform a list of dimension indices and symbols into a list of results, with affine expressions combining the indices and symbols. Affine maps distinguish between indices and symbols because indices are inputs to the affine map when the map is called (through an operation such as affine.apply ), whereas symbols are bound when the map is established (e.g. when a memref is formed, establishing a memory layout map ).

Affine maps are used for various core structures in MLIR. The restrictions we impose on their form allows powerful analysis and transformation, while keeping the representation closed with respect to several operations of interest.

Named affine mappings

Syntax:

affine-map-id ::= `#` suffix-id

// Definitions of affine maps are at the top of the file.
affine-map-def    ::= affine-map-id `=` affine-map-inline
module-header-def ::= affine-map-def

// Uses of affine maps may use the inline form or the named form.
affine-map ::= affine-map-id | affine-map-inline

Affine mappings may be defined inline at the point of use, or may be hoisted to the top of the file and given a name with an affine map definition, and used by name.

Examples:

// Affine map out-of-line definition and usage example.
#affine_map42 = affine_map<(d0, d1)[s0] -> (d0, d0 + d1 + s0 floordiv 2)>

// Use an affine mapping definition in an alloc operation, binding the
// SSA value %N to the symbol s0.
%a = alloc()[%N] : memref<4x4xf32, #affine_map42>

// Same thing with an inline affine mapping definition.
%b = alloc()[%N] : memref<4x4xf32, affine_map<(d0, d1)[s0] -> (d0, d0 + d1 + s0 floordiv 2)>>

Semi-affine maps

Semi-affine maps are extensions of affine maps to allow multiplication, floordiv, ceildiv, and mod with respect to symbolic identifiers. Semi-affine maps are thus a strict superset of affine maps.

Syntax of semi-affine expressions:

semi-affine-expr ::= `(` semi-affine-expr `)`
                   | semi-affine-expr `+` semi-affine-expr
                   | semi-affine-expr `-` semi-affine-expr
                   | symbol-or-const `*` semi-affine-expr
                   | semi-affine-expr `ceildiv` symbol-or-const
                   | semi-affine-expr `floordiv` symbol-or-const
                   | semi-affine-expr `mod` symbol-or-const
                   | bare-id
                   | `-`? integer-literal

symbol-or-const ::= `-`? integer-literal | symbol-id

multi-dim-semi-affine-expr ::= `(` semi-affine-expr (`,` semi-affine-expr)* `)`

The precedence and associativity of operations in the syntax above is the same as that for affine expressions .

Syntax of semi-affine maps:

semi-affine-map-inline
   ::= dim-and-symbol-id-lists `->` multi-dim-semi-affine-expr

Semi-affine maps may be defined inline at the point of use, or may be hoisted to the top of the file and given a name with a semi-affine map definition, and used by name.

semi-affine-map-id ::= `#` suffix-id

// Definitions of semi-affine maps are at the top of file.
semi-affine-map-def ::= semi-affine-map-id `=` semi-affine-map-inline
module-header-def ::= semi-affine-map-def

// Uses of semi-affine maps may use the inline form or the named form.
semi-affine-map ::= semi-affine-map-id | semi-affine-map-inline

Integer Sets

An integer set is a conjunction of affine constraints on a list of identifiers. The identifiers associated with the integer set are separated out into two classes: the set’s dimension identifiers, and the set’s symbolic identifiers. The set is viewed as being parametric on its symbolic identifiers. In the syntax, the list of set’s dimension identifiers are enclosed in parentheses while its symbols are enclosed in square brackets.

Syntax of affine constraints:

affine-constraint ::= affine-expr `>=` `0`
                    | affine-expr `==` `0`
affine-constraint-conjunction ::= affine-constraint (`,` affine-constraint)*

Integer sets may be defined inline at the point of use, or may be hoisted to the top of the file and given a name with an integer set definition, and used by name.

integer-set-id ::= `#` suffix-id

integer-set-inline
   ::= dim-and-symbol-id-lists `:` '(' affine-constraint-conjunction? ')'

// Declarations of integer sets are at the top of the file.
integer-set-decl ::= integer-set-id `=` integer-set-inline

// Uses of integer sets may use the inline form or the named form.
integer-set ::= integer-set-id | integer-set-inline

The dimensionality of an integer set is the number of identifiers appearing in dimension list of the set. The affine-constraint non-terminals appearing in the syntax above are only allowed to contain identifiers from dims and symbols. A set with no constraints is a set that is unbounded along all of the set’s dimensions.

Example:

// A example two-dimensional integer set with two symbols.
#set42 = affine_set<(d0, d1)[s0, s1]
   : (d0 >= 0, -d0 + s0 - 1 >= 0, d1 >= 0, -d1 + s1 - 1 >= 0)>

// Inside a Region
affine.if #set42(%i, %j)[%M, %N] {
  ...
}

d0 and d1 correspond to dimensional identifiers of the set, while s0 and s1 are symbol identifiers.

Operations

affine.apply (AffineApplyOp)

affine apply operation

The affine.apply operation applies an affine mapping to a list of SSA values, yielding a single SSA value. The number of dimension and symbol arguments to affine.apply must be equal to the respective number of dimensional and symbolic inputs to the affine mapping; the affine mapping has to be one-dimensional, and so the affine.apply operation always returns one value. The input operands and result must all have ‘index’ type.

Example:

#map10 = affine_map<(d0, d1) -> (d0 floordiv 8 + d1 floordiv 128)>
...
%1 = affine.apply #map10 (%s, %t)

// Inline example.
%2 = affine.apply affine_map<(i)[s0] -> (i+s0)> (%42)[%n]

Attributes:

AttributeMLIR TypeDescription
mapAffineMapAttrAffineMap attribute

Operands:

OperandDescription
mapOperandsindex

Results:

ResultDescription
«unnamed»index

affine.for (AffineForOp)

for operation

Syntax:

operation   ::= `affine.for` ssa-id `=` lower-bound `to` upper-bound
                (`step` integer-literal)? `{` op* `}`

lower-bound ::= `max`? affine-map-attribute dim-and-symbol-use-list | shorthand-bound
upper-bound ::= `min`? affine-map-attribute dim-and-symbol-use-list | shorthand-bound
shorthand-bound ::= ssa-id | `-`? integer-literal

The affine.for operation represents an affine loop nest. It has one region containing its body. This region must contain one block that terminates with affine.terminator . Note: when affine.for is printed in custom format, the terminator is omitted. The block has one argument of index type that represents the induction variable of the loop.

The affine.for operation executes its body a number of times iterating from a lower bound to an upper bound by a stride. The stride, represented by step, is a positive constant integer which defaults to “1” if not present. The lower and upper bounds specify a half-open range: the range includes the lower bound but does not include the upper bound.

The lower and upper bounds of a affine.for operation are represented as an application of an affine mapping to a list of SSA values passed to the map. The same restrictions hold for these SSA values as for all bindings of SSA values to dimensions and symbols.

The affine mappings for the bounds may return multiple results, in which case the max/min keywords are required (for the lower/upper bound respectively), and the bound is the maximum/minimum of the returned values. There is no semantic ambiguity, but MLIR syntax requires the use of these keywords to make things more obvious to human readers.

Many upper and lower bounds are simple, so MLIR accepts two custom form syntaxes: the form that accepts a single ‘ssa-id’ (e.g. %N) is shorthand for applying that SSA value to a function that maps a single symbol to itself, e.g., ()[s]->(s)()[%N]. The integer literal form (e.g. -42) is shorthand for a nullary mapping function that returns the constant value (e.g. ()->(-42)()).

Example showing reverse iteration of the inner loop:

#map57 = affine_map<(d0)[s0] -> (s0 - d0 - 1)>

func @simple_example(%A: memref<?x?xf32>, %B: memref<?x?xf32>) {
  %N = dim %A, 0 : memref<?x?xf32>
  affine.for %i = 0 to %N step 1 {
    affine.for %j = 0 to %N {   // implicitly steps by 1
      %0 = affine.apply #map57(%j)[%N]
      %tmp = call @F1(%A, %i, %0) : (memref<?x?xf32>, index, index)->(f32)
      call @F2(%tmp, %B, %i, %0) : (f32, memref<?x?xf32>, index, index)->()
    }
  }
  return
}

Operands:

OperandDescription
«unnamed»any type

affine.if (AffineIfOp)

if-then-else operation

Syntax:

operation  ::= `affine.if` if-op-cond `{` op* `}` (`else` `{` op* `}`)?
if-op-cond ::= integer-set-attr dim-and-symbol-use-list

The affine.if operation restricts execution to a subset of the loop iteration space defined by an integer set (a conjunction of affine constraints). A single affine.if may end with an optional else clause.

The condition of the affine.if is represented by an integer set (a conjunction of affine constraints), and the SSA values bound to the dimensions and symbols in the integer set. The same restrictions hold for these SSA values as for all bindings of SSA values to dimensions and symbols.

The affine.if operation contains two regions for the “then” and “else” clauses. The latter may be empty (i.e. contain no blocks), meaning the absence of the else clause. When non-empty, both regions must contain exactly one block terminating with affine.terminator . Note: when affine.if is printed in custom format, the terminator is omitted. These blocks must not have any arguments.

Example:

#set = affine_set<(d0, d1)[s0]: (d0 - 10 >= 0, s0 - d0 - 9 >= 0,
                                 d1 - 10 >= 0, s0 - d1 - 9 >= 0)>
func @reduced_domain_example(%A, %X, %N) : (memref<10xi32>, i32, i32) {
  affine.for %i = 0 to %N {
     affine.for %j = 0 to %N {
       %0 = affine.apply #map42(%j)
       %tmp = call @S1(%X, %i, %0)
       affine.if #set(%i, %j)[%N] {
          %1 = affine.apply #map43(%i, %j)
          call @S2(%tmp, %A, %i, %1)
       }
    }
  }
  return
}

Operands:

OperandDescription
«unnamed»any type

affine.max (AffineMaxOp)

max operation

The “max” operation computes the maximum value result from a multi-result affine map.

Example:

%0 = affine.max (d0) -> (1000, d0 + 512) (%i0) : index

Attributes:

AttributeMLIR TypeDescription
mapAffineMapAttrAffineMap attribute

Operands:

OperandDescription
operandsindex

Results:

ResultDescription
«unnamed»index

affine.min (AffineMinOp)

min operation

Syntax:

operation ::= ssa-id `=` `affine.min` affine-map-attribute dim-and-symbol-use-list

The affine.min operation applies an affine mapping to a list of SSA values, and returns the minimum value of all result expressions. The number of dimension and symbol arguments to affine.min must be equal to the respective number of dimensional and symbolic inputs to the affine mapping; the affine.min operation always returns one value. The input operands and result must all have ‘index’ type.

Example:

%0 = affine.min affine_map<(d0)[s0] -> (1000, d0 + 512, s0)> (%arg0)[%arg1]

Attributes:

AttributeMLIR TypeDescription
mapAffineMapAttrAffineMap attribute

Operands:

OperandDescription
operandsindex

Results:

ResultDescription
«unnamed»index

affine.parallel (AffineParallelOp)

multi-index parallel band operation

The “affine.parallel” operation represents a hyper-rectangular affine parallel band, defining multiple SSA values for its induction variables. It has one region capturing the parallel band body. The induction variables are represented as arguments of this region. These SSA values always have type index, which is the size of the machine word. The strides, represented by steps, are positive constant integers which defaults to “1” if not present. The lower and upper bounds specify a half-open range: the range includes the lower bound but does not include the upper bound. The body region must contain exactly one block that terminates with “affine.terminator”.

The lower and upper bounds of a parallel operation are represented as an application of an affine mapping to a list of SSA values passed to the map. The same restrictions hold for these SSA values as for all bindings of SSA values to dimensions and symbols.

Note: Calling AffineParallelOp::build will create the required region and block, and insert the required terminator. Parsing will also create the required region, block, and terminator, even when they are missing from the textual representation.

Example:

affine.parallel (%i, %j) = (0, 0) to (10, 10) step (1, 1) {
  ...
}

Attributes:

AttributeMLIR TypeDescription
lowerBoundsMapAffineMapAttrAffineMap attribute
upperBoundsMapAffineMapAttrAffineMap attribute
stepsArrayAttr64-bit integer array attribute

Operands:

OperandDescription
mapOperandsindex

affine.prefetch (AffinePrefetchOp)

affine prefetch operation

The “affine.prefetch” op prefetches data from a memref location described with an affine subscript similar to affine.load, and has three attributes: a read/write specifier, a locality hint, and a cache type specifier as shown below:

affine.prefetch %0[%i, %j + 5], read, locality<3>, data : memref<400x400xi32>

The read/write specifier is either ‘read’ or ‘write’, the locality hint specifier ranges from locality<0> (no locality) to locality<3> (extremely local keep in cache). The cache type specifier is either ‘data’ or ‘instr’ and specifies whether the prefetch is performed on data cache or on instruction cache.

Attributes:

AttributeMLIR TypeDescription
isWriteBoolAttrbool attribute
localityHintIntegerAttr32-bit signless integer attribute whose minimum value is 0 whose maximum value is 3
isDataCacheBoolAttrbool attribute

Operands:

OperandDescription
memrefmemref of any type values
indicesindex

affine.terminator (AffineTerminatorOp)

affine terminator operation

Syntax:

operation ::= `"affine.terminator"() : () -> ()`

Affine terminator is a special terminator operation for blocks inside affine loops ( affine.for ) and branches ( affine.if ). It unconditionally transmits the control flow to the successor of the operation enclosing the region.

Rationale: bodies of affine operations are blocks that must have terminators. Loops and branches represent structured control flow and should not accept arbitrary branches as terminators.

This operation does not have a custom syntax. However, affine control operations omit the terminator in their custom syntax for brevity.

‘affine.load’ operation

Syntax:

operation ::= ssa-id `=` `affine.load` ssa-use `[` multi-dim-affine-map-of-ssa-ids `]` `:` memref-type

The affine.load op reads an element from a memref, where the index for each memref dimension is an affine expression of loop induction variables and symbols. The output of ‘affine.load’ is a new value with the same type as the elements of the memref. An affine expression of loop IVs and symbols must be specified for each dimension of the memref. The keyword ‘symbol’ can be used to indicate SSA identifiers which are symbolic.

Example:


  Example 1:

    %1 = affine.load %0[%i0 + 3, %i1 + 7] : memref<100x100xf32>

  Example 2: Uses 'symbol' keyword for symbols '%n' and '%m'.

    %1 = affine.load %0[%i0 + symbol(%n), %i1 + symbol(%m)]
      : memref<100x100xf32>

‘affine.store’ operation

Syntax:

operation ::= ssa-id `=` `affine.store` ssa-use, ssa-use `[` multi-dim-affine-map-of-ssa-ids `]` `:` memref-type

The affine.store op writes an element to a memref, where the index for each memref dimension is an affine expression of loop induction variables and symbols. The ‘affine.store’ op stores a new value which is the same type as the elements of the memref. An affine expression of loop IVs and symbols must be specified for each dimension of the memref. The keyword ‘symbol’ can be used to indicate SSA identifiers which are symbolic.

Example:


    Example 1:

      affine.store %v0, %0[%i0 + 3, %i1 + 7] : memref<100x100xf32>

    Example 2: Uses 'symbol' keyword for symbols '%n' and '%m'.

      affine.store %v0, %0[%i0 + symbol(%n), %i1 + symbol(%m)]
        : memref<100x100xf32>

‘affine.dma_start’ operation

Syntax:

operation ::= `affine.dma_Start` ssa-use `[` multi-dim-affine-map-of-ssa-ids `]`, `[` multi-dim-affine-map-of-ssa-ids `]`, `[` multi-dim-affine-map-of-ssa-ids `]`, ssa-use `:` memref-type

The affine.dma_start op starts a non-blocking DMA operation that transfers data from a source memref to a destination memref. The source and destination memref need not be of the same dimensionality, but need to have the same elemental type. The operands include the source and destination memref’s each followed by its indices, size of the data transfer in terms of the number of elements (of the elemental type of the memref), a tag memref with its indices, and optionally at the end, a stride and a number_of_elements_per_stride arguments. The tag location is used by an AffineDmaWaitOp to check for completion. The indices of the source memref, destination memref, and the tag memref have the same restrictions as any affine.load/store. In particular, index for each memref dimension must be an affine expression of loop induction variables and symbols. The optional stride arguments should be of ‘index’ type, and specify a stride for the slower memory space (memory space with a lower memory space id), transferring chunks of number_of_elements_per_stride every stride until %num_elements are transferred. Either both or no stride arguments should be specified. The value of ‘num_elements’ must be a multiple of ‘number_of_elements_per_stride’.

Example:

For example, a DmaStartOp operation that transfers 256 elements of a memref
'%src' in memory space 0 at indices [%i + 3, %j] to memref '%dst' in memory
space 1 at indices [%k + 7, %l], would be specified as follows:

  %num_elements = constant 256
  %idx = constant 0 : index
  %tag = alloc() : memref<1xi32, 4>
  affine.dma_start %src[%i + 3, %j], %dst[%k + 7, %l], %tag[%idx],
    %num_elements :
      memref<40x128xf32, 0>, memref<2x1024xf32, 1>, memref<1xi32, 2>

  If %stride and %num_elt_per_stride are specified, the DMA is expected to
  transfer %num_elt_per_stride elements every %stride elements apart from
  memory space 0 until %num_elements are transferred.

  affine.dma_start %src[%i, %j], %dst[%k, %l], %tag[%idx], %num_elements,
    %stride, %num_elt_per_stride : ...

‘affine.dma_wait’ operation

Syntax:

operation ::= `affine.dma_Start` ssa-use `[` multi-dim-affine-map-of-ssa-ids `]`, `[` multi-dim-affine-map-of-ssa-ids `]`, `[` multi-dim-affine-map-of-ssa-ids `]`, ssa-use `:` memref-type

The affine.dma_start op blocks until the completion of a DMA operation associated with the tag element ‘%tag[%index]'. %tag is a memref, and %index has to be an index with the same restrictions as any load/store index. In particular, index for each memref dimension must be an affine expression of loop induction variables and symbols. %num_elements is the number of elements associated with the DMA operation. For example:

Example:

affine.dma_start %src[%i, %j], %dst[%k, %l], %tag[%index], %num_elements :
  memref<2048xf32, 0>, memref<256xf32, 1>, memref<1xi32, 2>
...
...
affine.dma_wait %tag[%index], %num_elements : memref<1xi32, 2>